CCCC Wuhan Harbour Engineering Design and Research (China)

Ultra-long and large-diameter underwater bored piles are widely used in deep-water bridge foundations; however, key construction parameters such as concrete surface elevation and tremie conduit embedment depth are still largely measured manually, resulting in low levels of automation and limited data traceability. Accurate monitoring of these parameters is essential to ensure construction quality and prevent defects such as pile breakage or mud inclusion. This study aims to develop an intelligent monitoring system to achieve real-time and automated measurement of concrete pouring height and conduit embedment depth during underwater pile construction. An integrated intelligent sensing system was developed combining fiber Bragg grating (FBG) pressure sensors, distributed fiber optic temperature sensing (DTS), RFID-based conduit counting, and a PLC-controlled automated monitoring device. Laboratory experiments and field tests were conducted to evaluate the feasibility of fiber optic pressure and temperature sensing for detecting the concrete interface. Laboratory tests demonstrated that fiber optic pressure and temperature sensors can effectively identify the interface between mud, laitance, and concrete during pouring. Field experiments showed that concrete level monitoring based on intelligent sensing achieved an error ranging from 0.25 m to 0.5 m, while dynamic tracking of the concrete surface achieved accuracy within approximately 0.3 m. The system was successfully applied in the Hangzhou Bay Cross-Sea Bridge project, confirming its reliability in engineering practice. The proposed monitoring system significantly improves the automation and informatization of underwater bored pile construction. Compared with traditional manual sounding methods, it provides higher monitoring frequency, improved accuracy, and real-time data transmission through a cloud platform, enabling traceable management of concealed works. The system offers a practical and cost-effective solution for intelligent construction of deep foundations and supports the digital transformation of pile foundation engineering.

Conventional Fiber-Reinforced Polymer (FRP) materials may exhibit certain performance uncertainties in harsh environments, limiting their reliability for structural strengthening. To address this, Basalt Fiber-Reinforced Polymer (BFRP) plates fabricated with silicate-modified epoxy resin are proposed for the flexural strengthening of reinforced concrete (RC) beams. The research aims to evaluate their short-term strengthening performance and establish a reliable calculation method for flexural capacity. Four-point bending tests were conducted to investigate the effects of BFRP plate thickness and end anchorage configuration on failure modes, flexural capacity, and ductility. Finite element simulations incorporating interfacial bond–slip behavior reproduced typical debonding failures, followed by a comprehensive parametric analysis. Based on the experimental and numerical results, a modified BFRP plate strain formula at debonding was proposed to establish a calculation method for the flexural capacity of BFRP-strengthened beams governed by debonding failure. The results indicate that beams without end anchorage were prone to interfacial debonding, where increasing the plate thickness from 0.5 mm to 2 mm raised the flexural capacity gain from 4.5% to 15% but intensified the ductility reduction from 42.9% to 64.9%. Conversely, applying mechanical anchorage improved the ductility index by over 20% compared to unanchored counterparts. The adopted FRP–concrete bond–slip constitutive model accurately characterizes interfacial debonding behavior, and the proposed flexural capacity model demonstrates high accuracy with overall deviations within 5%. It can be concluded that the novel BFRP plates exhibit strengthening behavior comparable to existing FRP systems. Effective end anchorage further enhances flexural capacity and prevents brittle failure. The proposed debonding strain formula for the novel BFRP system offers a reliable basis for capturing the critical onset of interfacial failure. Building upon this, the developed flexural capacity model provides a reliable theoretical basis for the design and assessment of RC beams strengthened with the novel BFRP plates.

Abstract Semi-flexible pavement (SFP) materials are known for their outstanding rutting resistance; however, their applications to new pavements are limited due to uncertainties in their structural bearing capacity and cracking behavior. In this respect, the structural performance and meso-scale cracking failure of semi-flexible pavement material have been investigated through a finite element analysis. A three-dimensional pavement model has been developed to investigate the influence of the SFP layer thickness, its placing position, and material modulus on bearing capacity. Meanwhile, a two-dimensional microstructure model, which is reconstructed from computed tomography scanning, is used to simulate indirect tensile tests and crack propagation within the specimens. The results show that by increasing SFP thickness from 4 cm to 18 cm, the vertical displacement reduced by about 32%, and most of the shear stress was confined to the near-surface layer, which enhances the rutting resistance significantly. It is noted that aggregate gradation and distribution are crucial for cracking resistance; specimens with finely graded aggregate showed more tortuous crack paths and superior post-peak ductility compared to those with low aggregate content and weak interlocking. The subgrade modulus variation has been found to have a decisive role in the total vertical displacement; when it decreased from 60 MPa to 40 MPa, there was a 16.7% increase in vertical displacement.

Soluble rocks such as limestone and dolomite can form karst features, including caves, sinkholes, and solution grooves through prolonged groundwater erosion (Parise et al., 2015). Karst landscapes are widespread globally. Construction in karst areas often faces sudden and severe ground collapse risks, endangering project safety, structural integrity, and personnel well-being. Therefore, the detection, assessment, and treatment of karst formations are crucial in engineering.Geotechnical investigation in karst regions necessarily includes karst detection. Current methods are diverse, primarily comprising geological mapping, engineering drilling, and geophysical exploration (Li and Xiao, 2006;Goldscheider et al., 2011;Kaufmann, 2014). Among these, geophysical techniques impose relatively fewer constraints and are more widely applied. Wang et al. (2025a) detailed the principles and data processing methods of four geophysical exploration approaches for karst detection: multi-electrode resistivity, cross-hole electromagnetic wave computed tomography, microtremor survey, and ground-penetrating radar.They compared the applicability of each method through case studies. A novel one-shaped layout 3D electrical exploration model has been proposed for detecting karst groundwater channels, improving exploration efficiency by 85.9% over conventional methods while maintaining high accuracy (Wang et al., 2025b).Karst collapse, a common hazard in such regions, is characterized by strong concealment, abrupt occurrence, and high destructiveness, capable of causing sudden surface subsidence and damage to structures. Thus, assessing and predicting karst collapse is essential.Machine learning has been a transformative tool in addressing various science and technology problems (Qu et al. 2021, Qu et al. 2023) .For example, it has been used for predicting potential hazards in tunnel engineering (Zhang et al., 2025;Qu et al., 2025;Yuan et al., 2026). To address the need for high-precision karst collapse assessment, Wang et al. The mechanism of dynamic grouting with self-expanding slurry for water plugging in karst tunnels was examined by Zhan et al. (2025). Tang et al. (2025) revealed that karst water erosion causes grouting curtain leakage mainly due to severe degradation of cement-clay composites, which are less durable than pure cement grouts. The pressure filtration effect in karst areas significantly enhances the initial consolidation strength of grouted curtains, necessitating a revised life prediction model that incorporates this effect for accurate service life forecasting, as validated through experiments and field application (Yan et al., 2025). Yao et al. (2025) demonstrated that integrating high-density resistivity and frequency-division electrical resistivity tomography with geological methods provides an accurate, practical, and broadly applicable approach for diagnosing leakage risks in karst reservoir dams.Shield tunneling through karst strata poses risks such as shield machine sinking, head pitching, ground settlement or collapse, and excessive postconstruction settlement (Cheng et al., 2017), which can cause serious hazards, significant economic loss, and even casualties (Xie et al., 2025;Ou et al., 2025b).Based on a shield tunneling project in Shenzhen, China, Li et al. (2025) proposed a membrane-sleeve valve pipe grouting technique for reinforcing karst strata, building on conventional sleeve valve pipe grouting. They detailed its key construction points and process, with field tests confirming its applicability. A combined short straight-hole and wedge compound cut blasting scheme was proposed and tested in a hard rock tunnel (Tu et al., 2025). Various machine learning techniques have been leveraged to integrate geological records and tunneling parameters for predicting rock grades (Dang et al., 2025). Mechanistic analysis of TBM cutterhead-ground interaction under the mud build-up effect was explored by Wang et al. (2025d).Finally, we extend our gratitude to everyone who contributed to this special issue. Their contributions include not only theoretical breakthroughs but also the accumulation and sharing of practical engineering experience. Through their dedicated efforts, challenges in karst construction are being progressively overcome, providing valuable references and insights for similar projects.PL: Conceptualization, Writing-original draft. PC: Investigation, Writing review and editing. XS: Writing-review and editing. XF: Writingreview and editing. CZ: Writing-original draft.